Stoichiometric Variations and Impurity Distributions in CsPbBr<sub>3</sub> Single Crystals Grown via Different Methods
Bibliographic record
Abstract
The all-inorganic semiconducting perovskite cesium lead bromide, CsPbBr3, exhibits promising properties for ionizing radiation detection applications. This work focuses on the comparative study of stoichiometric variations and impurity distributions in CsPbBr3single crystals obtained from different crystal growth approaches. Single crystals of CsPbBr3were grown from room-temperature solution methods, modified high temperature zone-refining methods as well as from Bridgman–Stockbarger methods. The bulk material purity was confirmed by X-ray diffraction method, while wavelength-dispersive X-ray spectroscopy was used to probe the local stoichiometry of the crystal. Laser ablation ICP-MS was employed to study the impurity distributions within crystal ingots. Photo-luminescence data was collected to identify the electrically active defect states. The observed intrinsic stoichiometric variations and extrinsic impurities were linked to the active defects identified by photo-luminescence spectroscopy. Finally, these material characterization results were correlated to the photo-electrical properties of the single crystal devices and the pulse height spectroscopy performances of the fabricated radiation detectors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".